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20192023
most citedNISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets

278 citations · 481 across the 19 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

eess.AS2023

Multi-dimensional Speech Quality Assessment in Crowdsourcing

Babak Naderi, Ross Cutler, Nicolae-Catalin Ristea

Subjective speech quality assessment is the gold standard for evaluating speech enhancement processing and telecommunication systems. The commonly used standard ITU-T Rec. P.800 de…

eess.IV2023★ 1 cited

Full Reference Video Quality Assessment for Machine Learning-Based Video Codecs

Abrar Majeedi, Babak Naderi, Yasaman Hosseinkashi +3

Machine learning-based video codecs have made significant progress in the past few years. A critical area in the development of ML-based video codecs is an accurate evaluation metr…

eess.IV2023

VCD: A Video Conferencing Dataset for Video Compression

Babak Naderi, Ross Cutler, Nabakumar Singh Khongbantabam +4

Commonly used datasets for evaluating video codecs are all very high quality and not representative of video typically used in video conferencing scenarios. We present the Video Co…

eess.IV2023

LSTM-based Video Quality Prediction Accounting for Temporal Distortions in Videoconferencing Calls

Gabriel Mittag, Babak Naderi, Vishak Gopal +1

Current state-of-the-art video quality models, such as VMAF, give excellent prediction results by comparing the degraded video with its reference video. However, they do not consid…

eess.AS2023

ICASSP 2023 Speech Signal Improvement Challenge

Ross Cutler, Ando Saabas, Babak Naderi +3

The ICASSP 2023 Speech Signal Improvement Challenge is intended to stimulate research in the area of improving the speech signal quality in communication systems. The speech signal…